OBJECTIVE To construct a dual-verification system integrating image pre-screening and Raman spectroscopy for inpatient pharmacy unit-dose dispensing in response to the issue of recognition blind spots for drugs of “same appearance but different spectrum” by drug inspection machines. METHODS An image feature and Raman spectroscopy database， covering 296 oral medications， were established. Spectral matching was performed using a cosine similarity algorithm （decision threshold 0.95）. A dual-verification system of “image pre-screening and Raman spectroscopy confirmation” was designed， and a self-controlled before-and-after study was conducted across 5 clinical wards. RESULTS The system achieved a mean recognition accuracy of 99.2% for all medications in the database， with 100% accurate identification of representative “same-appearance but different-spectrum” drugs. The average verification time per-unit in the experimental group （image recognition+Raman spectroscopy confirmation and verification） was reduced by 31.5%-43.3%， compared with the control group （image recognition+manual visual comparison with actual objects）（ P ＜0.001）. Nurses’ satisfaction scores in the dimensions of operational convenience， identification efficiency， verification confidence， and psychological stress relief in the experimental group were all significantly superior to those of the control group （ P ＜0.01）. CONCLUSIONS The dual-verification system of “image pre-screening and Raman spectroscopy confirmation” effectively overcomes the technical limitations of conventional machine vision. It enhances work efficiency and staff satisfaction while ensuring medication safety.